Instructions to use lora-library/https-huggingface-co-lora-library-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/https-huggingface-co-lora-library-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/https-huggingface-co-lora-library-test") prompt = "Ping hair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ab32fb71691185d501438a5996f7b894f676b012ffe32499bfc65293487df952
- Size of remote file:
- 3.49 MB
- SHA256:
- e65b3ec174c2da570fcb7bea15b870be332e841e0002480940c264e35985639f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.